Meeting Summaries And Task Extractor
When a Fireflies.ai meeting ends, it summarizes the transcript via Gemini and posts the recap to Slack while creating tasks in ClickUp.
ops and IT teamsdevelopers and engineers
What it does
Get meeting recaps and organized task lists instantly after your Fireflies.ai calls end. You receive a concise summary posted to Slack while action items are automatically created as tasks in ClickUp using Google Gemini.
Step by step
- Configure a webhook listener in your application to receive POST requests from Fireflies.ai upon meeting completion.
- Implement an HTTP client function that accepts the transcript ID and API key to fetch the raw text content from the Fireflies endpoint.
- Define a strict JSON schema for the output containing fields for summary, action items, assignees, and due dates.
- Write separate integration modules using official SDKs or REST endpoints for Slack chat.postMessage and ClickUp task creation.
Where the LLM does the work
- Prompt Google Gemini to analyze the raw transcript and extract specific action items with clear owners and deadlines from ambiguous conversation context.
- Instruct the model to condense lengthy discussions into a concise executive summary while preserving key decisions and technical details.
- Refine the generated JSON structure to ensure it matches the required schema for downstream automation without manual intervention.
Watch out for
Transcripts can exceed token limits so you must implement chunking or summarization strategies before sending data to the LLM.
ClickUp task creation might fail if assignee IDs are missing so validate user mappings against your organization's directory beforehand.
Webhook signatures can be spoofed so verify the Fireflies secret signature on every incoming request to ensure security.
Tools that fit
Google Gemini Chat Model LLM Summarization and action item extraction
Code API Pre-processing and JSON formatting
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Meeting Summaries And Task Extractor: When a Fireflies.ai meeting ends, it summarizes the transcript via Gemini and posts the recap to Slack while creating tasks in ClickUp. ## Specification - What it does: Get meeting recaps and organized task lists instantly after your Fireflies.ai calls end. You receive a concise summary posted to Slack while action items are automatically created as tasks in ClickUp using Google Gemini. - Trigger: Triggered by an event (Event · on meeting transcription complete) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - Fireflies.ai: Trigger and transcript retrieval - Google Gemini Chat Model: Summarization and action item extraction - Code: Pre-processing and JSON formatting - Slack: Posting meeting summaries - ClickUp: Creating action item tasks ## Known pitfalls, handle each one explicitly in your implementation 1. Transcripts can exceed token limits so you must implement chunking or summarization strategies before sending data to the LLM. 2. ClickUp task creation might fail if assignee IDs are missing so validate user mappings against your organization's directory beforehand. 3. Webhook signatures can be spoofed so verify the Fireflies secret signature on every incoming request to ensure security. ## Reference implementation https://n8n.io/workflows/8592 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/meeting-summaries-and-task-extractor/ via usecasesforagents.com
Frequently asked questions
Can I use a different Transcription than Fireflies.ai?
Yes. Fireflies.ai is only the example transcription in this recipe. The same flow works with AssemblyAI, Google Text-to-Speech API, MeetGeek API and OCR.space. Swap the transcription connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for Ops-IT teams who need one more recurring task off a human's plate.
Developers can adapt this to their own repo or ticket queue with the same trigger and tools.